World's Best Scientists 2026 revealed!
Abderrahim Jardani

Abderrahim Jardani

D-Index & Metrics

Earth Science

D-Index
39
Citations
4185
World Ranking
6313
National Ranking
479

Overview

Abderrahim Jardani is affiliated with the University of Rouen in France and has a research focus spanning environmental science, engineering, and earth and planetary sciences. Their work extensively covers areas such as groundwater flow and contamination studies, seismic imaging and inversion techniques, hydrology and watershed management studies, and geophysical and geoelectrical methods.

The scientist's notable recent publications include:

  • Use of convolutional neural networks with encoder-decoder structure for predicting the inverse operator in hydraulic tomography, 2021, Journal of Hydrology
  • Reconstruction of missing groundwater level data by using Long Short-Term Memory (LSTM) deep neural network, 2020, Journal of Hydrology
  • Convolutional neural networks with SegNet architecture applied to three-dimensional tomography of subsurface electrical resistivity: CNN-3D-ERT, 2021, Geophysical Journal International
  • A wavelet-assisted deep learning approach for simulating groundwater levels affected by low-frequency variability, 2022, The Science of The Total Environment
  • Hydraulic tomography in coupled discrete-continuum concept to image hydraulic properties of a fractured and karstified aquifer (Lez aquifer, France), 2020, Advances in Water Resources

Jardani frequently publishes in several key venues including Journal of Hydrology, SSRN Electronic Journal, The Science of The Total Environment, Geophysical Journal International, and Advances in Water Resources.

The scientist collaborates regularly with a number of co-authors. Frequent collaborators include:

  • M.T. Vu
  • Nicolas Masséi
  • Pierre Fischer
  • Sivarama Krishna Reddy Chidepudi
  • Abel Henriot

Their research interests intersect various subfields such as environmental engineering, geophysics, ocean engineering, water science and technology, and global and planetary change. This multidimensional approach reflects in their work on hydrological forecasting using AI and hydraulic fracturing and reservoir analysis.

Abderrahim Jardani's contributions to hydraulic tomography and geophysical methods are characterized by the use of advanced deep learning techniques, including convolutional neural networks and long short-term memory models, to address complex problems in hydrology and groundwater studies.

Best Publications

  • OZCAR: The French Network of Critical Zone Observatories

    J. Gaillardet;I. Braud;F. Hankard;S. Anquetin

  • The Self-Potential Method: Theory and Applications in Environmental Geosciences

    André Revil;Abderrahim Jardani

  • Tomography of the Darcy velocity from self-potential measurements

    Abderrahim Jardani;A. Revil;A. Revil;A. Boleve;A. Crespy

  • The Self-Potential Method

    Unknown

  • Reconstruction of missing groundwater level data by using Long Short-Term Memory (LSTM) deep neural network

    M.T. Vu;A. Jardani;N. Massei;M. Fournier

  • Three-dimensional inversion of self-potential data used to constrain the pattern of groundwater flow in geothermal fields

    Abderrahim Jardani;A. Revil;A. Boleve;Jean-Paul Dupont

  • Stochastic joint inversion of hydrogeophysical data for salt tracer test monitoring and hydraulic conductivity imaging

    Abderrahim Jardani;A. Revil;A. Revil;Jean-Paul Dupont

  • Seismoelectric response of heavy oil reservoirs: theory and numerical modelling

    A. Revil;Abderrahim Jardani

  • Self-potential signals associated with preferential groundwater flow pathways in sinkholes

    Abderrahim Jardani;Jean-Paul Dupont;A. Revil

  • Reconstruction of the water table from self-potential data: a bayesian approach.

    A. Jardani;A. Revil;Warren Barrash;A. Crespy

  • Detection of preferential infiltration pathways in sinkholes using joint inversion of self‐potential and EM‐34 conductivity data

    A. Jardani;A. Revil;F. Santos;C. Fauchard

  • Saline pulse test monitoring with the self-potential method to nonintrusively determine the velocity of the pore water in leaking areas of earth dams and embankments

    S. J. Ikard;A. Revil;A. Revil;Abderrahim Jardani;W. F. Woodruff

  • Forward Modeling and validation of a new formulation to compute self-potential signals associated with ground water flow

    A. Bolève;A. Revil;A. Revil;F. Janod;J. L. Mattiuzzo

  • Stochastic joint inversion of 2D seismic and seismoelectric signals in linear poroelastic materials: A numerical investigation

    Abderrahim Jardani;André Revil;André Revil;Evert Slob;Evert Slob;Walter Söllner

  • Stochastic joint inversion of temperature and self-potential data

    Abderrahim Jardani;A. Revil;A. Revil

  • A new model for the spectral induced polarization signature of bacterial growth in porous media

    Andre Revil;Andre Revil;Estella A. Atekwana;C. Zhang;Abderrahim Jardani

  • Seismoelectric coupling in unsaturated porous media: theory, petrophysics, and saturation front localization using an electroacoustic approach

    A Revil;G Barnier;M Karaoulis;P Sava

  • Self-potential monitoring of a salt plume

    P. Martínez-Pagán;A. Jardani;A. Revil;A. Haas

  • Detection and localization of hydromechanical disturbances in a sandbox using the self‐potential method

    A. Crespy;A. Revil;N. Linde;S. Byrdina

  • Hydraulic conductivity field characterization from the joint inversion of hydraulic heads and self‐potential data

    A Soueid Ahmed;Abderrahim Jardani;A Revil;A Revil;Jean-Paul Dupont

  • Self‐potential tomography applied to the determination of cavities

    Abderrahim Jardani;A. Revil;Jean-Paul Dupont

  • SNO KARST: a French network of observatories for the multidisciplinary study of critical zone processes in karst watersheds and aquifers

    H. Jourde;N. Massei;N. Mazzilli;S. Binet

Frequent Co-Authors

André Revil
André Revil Université Savoie Mont Blanc
Hervé Jourde
Hervé Jourde University of Montpellier
Paul Sava
Paul Sava Colorado School of Mines
Warren Barrash
Warren Barrash Boise State University
David Labat
David Labat Géosciences Environnement Toulouse
Tian-Chyi Jim Yeh
Tian-Chyi Jim Yeh University of Arizona
Niklas Linde
Niklas Linde University of Lausanne
Anne Probst
Anne Probst Paul Sabatier University
Jean-Luc Probst
Jean-Luc Probst Paul Sabatier University
Shemin Ge
Shemin Ge University of Colorado Boulder

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Earth Science opens diverse career pathways, but many students also explore complementary fields to broaden their opportunities. For instance, veterans interested in expanding their skill sets might find valuable options through a spanish degree online for veterans, which can enhance communication abilities in global environmental projects.

Creative professionals passionate about the environment may pursue an mfa degree online to combine scientific knowledge with artistic expression, improving public awareness about Earth science topics.

For those aiming to step into leadership roles, online masters programs in human resource management provide essential skills in managing organizational dynamics within environmental agencies or research institutions. Learn more about online masters programs in human resource management.

Seniors looking to shift careers or update their credentials can benefit from one year degrees for seniors, which offer flexible, accelerated options aligning with life science interests.

Best Scientists Citing Abderrahim Jardani

Trending Scientists

Recently Published Articles